Power amplifiers are known to distort the signal they are designed to amplify. The reason for this is that a power amplifier has a non-linear input-output signal characteristic. This shows up as a broadened spectrum around the desired amplified signal, and as an unwanted inband component of the signal. As a counter-measure to decrease the effects of non-linearity, it is known to pre-distort the signal at the input of the amplifier as to give an un-distorted amplified signal at the output of the amplifier. This technique is called pre-distortion. Pre-distortion as implemented today normally uses a look-up table that is used to multiply the signal. The entry into the table is the magnitude of the signal at every time sample.
A variation of the single look-up table approach for handling non-linearity is described in [1]. Here a FIR filter is used to handle both non-linearity and inter-symbol interference. Instead of performing the filter coefficient multiplication at each filter tap explicitly, look-up tables are used to perform this task.
Memory effects is another problem related to power amplifiers. Memory effects typically show up as a non-symmetrical spectrum around the carrier at the output of a power amplifier. That is, although the carrier (desired signal) spectrum is perfectly symmetrical, the spurious spectrum coming from the distortion may be non-symmetrical with respect to the center of the carrier.
The methods used to handle non-linearity do not take into account memory effects of the power amplifier. As the term “memory effects” indicates, there is a dependence not only on the present sample but also on previous samples of the signal. Thus, the previously used single table approach cannot take care of memory effects, but can only handle non-linearity.
Reference [2] suggests handling memory effects by using an envelope filter, which considers both the current and previous sample amplitudes in calculating a weighted multiplication coefficient that is intended to account for memory effects.
Lei Ding et. al. [3] inspired by work done by Kim and Konstantinou [4] have derived a pre-distortion method based on what they call “Memory Polynomials” that very well model memory effects. However, this method has the drawback that it requires recalculation of the memory polynomials for each new input signal amplitude, which can be computationally costly, especially if many polynomials of high order are used.